Open Access
Review
Issue
Vis Cancer Med
Volume 5, 2024
Article Number 4
Number of page(s) 9
DOI https://doi.org/10.1051/vcm/2024004
Published online 22 May 2024
  1. Wisdom AJ, Hong CS, Lin AJ, Xiang Y, Cooper DE, Zhang J, et al. Neutrophils promote tumor resistance to radiation therapy. Proc Natl Acad Sci USA. 2019;116(37):18584–18589. [CrossRef] [PubMed] [Google Scholar]
  2. Knopf AC, Lomax A. In vivo proton range verification: A review. Phys Med Biol. 2013;58(15):R131–R160. [CrossRef] [PubMed] [Google Scholar]
  3. Paganetti H. Range uncertainties in proton therapy and the role of Monte Carlo simulations. Phys Med Biol. 2012;57(11):R99–R117. [CrossRef] [PubMed] [Google Scholar]
  4. Fukumitsu N, Sugahara S, Nakayama H, Fukuda K, Mizumoto M, Abei M, et al. A prospective study of hypofractionated proton beam therapy for patients with hepatocellular carcinoma. Int J Radiat Oncol Biol Phys. 2009;74(3):831–836. [CrossRef] [PubMed] [Google Scholar]
  5. Liao Z, Lee JJ, Komaki R, Gomez DR, O’Reilly MS, Fossella FV, et al. Bayesian adaptive randomization trial of passive scattering proton therapy and intensity-modulated photon radiotherapy for locally advanced non-small-cell lung cancer. J Clin Oncol. 2018;36(18):1813–1822. [CrossRef] [PubMed] [Google Scholar]
  6. Saeed AM, Khairnar R, Sharma AM, Larson GL, Tsai HK, Wang CJ, et al. Clinical outcomes in patients with recurrent glioblastoma treated with proton beam therapy reirradiation: Analysis of the multi-institutional proton collaborative group registry. Adv Radiat Oncol. 2020;5(5):978–983. [CrossRef] [PubMed] [Google Scholar]
  7. Giaddui T, Chen W, Yu J, Lin L, Simone CB, Yuan L, et al. Establishing the feasibility of the dosimetric compliance criteria of RTOG 1308: Phase III randomized trial comparing overall survival after photon versus proton radiochemotherapy for inoperable stage II-IIIB NSCLC. Radiat Oncol. 2016;4(11):66. [CrossRef] [PubMed] [Google Scholar]
  8. Parzen JS, Hartsell W, Chang J, Apisarnthanarax S, Molitoris J, Durci M, et al. Hypofractionated proton beam radiotherapy in patients with unresectable liver tumors: Multi-institutional prospective results from the Proton Collaborative Group. Radiat Oncol. 2020;15(1):255. [CrossRef] [PubMed] [Google Scholar]
  9. Kim TH, Park JW, Kim BH, Oh ES, Youn SH, Moon SH, et al. Phase II study of hypofractionated proton beam therapy for hepatocellular carcinoma. Front Oncol. 2020;10:542. [Google Scholar]
  10. Lin SH, Hobbs BP, Verma V, Tidwell RS, Smith GL, Lei X, et al. Randomized phase IIB trial of proton beam therapy versus intensity-modulated radiation therapy for locally advanced esophageal cancer. J Clin Oncol. 2020;38(14):1569–1579. [CrossRef] [PubMed] [Google Scholar]
  11. Tseng YD, Hoppe BS, Dedeckova K, Patel CG, Hill-Kayser CE, Miller DM, et al. Risk of pneumonitis and outcomes after mediastinal proton therapy for relapsed/refractory lymphoma: A PTCOG and PCG collaboration. Int J Radiat Oncol Biol Phys. 2021;109(1):220–230. [CrossRef] [PubMed] [Google Scholar]
  12. Sugahara S, Kamada T, Imai R, Tsuji H, Kameda N, Okada T, et al. Carbon ion radiotherapy for localized primary sarcoma of the extremities: Results of a phase I/II trial. Radiother Oncol. 2012;105(2):226–231. [CrossRef] [PubMed] [Google Scholar]
  13. McNamara AL, Schuemann J, Paganetti H. A phenomenological relative biological effectiveness (RBE) model for proton therapy based on all published in vitro cell survival data. Phys Med Biol. 2015;60(21):8399–8416. [CrossRef] [PubMed] [Google Scholar]
  14. Paganetti H, Niemierko A, Ancukiewicz M, Gerweck LE, Goitein M, Loeffler JS, et al. Relative biological effectiveness (RBE) values for proton beam therapy. Int J Radiat Oncol Biol Phys. 2002;53(2):407–421. [CrossRef] [PubMed] [Google Scholar]
  15. Paganetti H. Relative biological effectiveness (RBE) values for proton beam therapy. Variations as a function of biological endpoint, dose, and linear energy transfer. Phys Med Biol. 2014;59(22):R419–R472. [CrossRef] [PubMed] [Google Scholar]
  16. Stewart RD, Carlson DJ, Butkus MP, Hawkins R, Friedrich T, Scholz M. A comparison of mechanism-inspired models for particle relative biological effectiveness (RBE). Med Phys. 2018;45(11):e925–e952. [CrossRef] [PubMed] [Google Scholar]
  17. Flanz J. Particle therapy technology for safe treatment. 1st ed. CRC Press. 2022. https://doi.org/10.1201/9781003123880. [Google Scholar]
  18. Trofimov A, Nguyen PL, Efstathiou JA, Wang Y, Lu HM, Engelsman M, et al. Interfractional variations in the setup of pelvic bony anatomy and soft tissue, and their implications on the delivery of proton therapy for localized prostate cancer. Int J Radiat Oncol Biol Phys. 2011;80(3):928–937. [CrossRef] [PubMed] [Google Scholar]
  19. Schneider U, Pedroni E, Lomax A. The calibration of CT Hounsfield units for radiotherapy treatment planning. Phys Med Biol. 1996;41(1):111–124. [CrossRef] [PubMed] [Google Scholar]
  20. Yang M, Zhu XR, Park PC, Titt U, Mohan R, Virshup G, et al. Comprehensive analysis of proton range uncertainties related to patient stopping-power-ratio estimation using the stoichiometric calibration. Phys Med Biol. 2012;57(13):4095–4115. [CrossRef] [PubMed] [Google Scholar]
  21. Zhang R, Baer E, Jee KW, Sharp GC, Flanz J, Lu HM. Investigation of real tissue water equivalent path lengths using an efficient dose extinction method. Phys Med Biol. 2017;62(14):5640–5651. [CrossRef] [PubMed] [Google Scholar]
  22. Zheng Y, Kang Y, Zeidan O, Schreuder N. An end-to-end assessment of range uncertainty in proton therapy using animal tissues. Phys Med Biol. 2016;61(22):8010–8024. [CrossRef] [PubMed] [Google Scholar]
  23. Taasti VT, Michalak GJ, Hansen DC, Deisher AJ, Kruse JJ, Krauss B, et al. Validation of proton stopping power ratio estimation based on dual energy CT using fresh tissue samples. Phys Med Biol. 2017;63(1):015012 [CrossRef] [PubMed] [Google Scholar]
  24. Xie Y, Ainsley C, Yin L, Zou W, McDonough J, Solberg TD, et al. Ex vivo validation of a stoichiometric dual energy CT proton stopping power ratio calibration. Phys Med Biol. 2018;63(5):055016. [CrossRef] [PubMed] [Google Scholar]
  25. Cui X, Jee K, Hu M, Bao J, Lu HM. Improvement of proton beam range uncertainty in breast treatment using tissue samples. Phys Med Biol. 2022;67(24):245006. [CrossRef] [Google Scholar]
  26. Meijers A, Free J, Wagenaar D, Deffet S, Knopf AC, Langendijk JA, et al. Validation of the proton range accuracy and optimization of CT calibration curves utilizing range probing. Phys Med Biol. 2020;65(3):03nt02. [Google Scholar]
  27. van Elmpt W, Landry G, Das M, Verhaegen F. Dual energy CT in radiotherapy: Current applications and future outlook. Radiother Oncol. 2016;119(1):137–144. [CrossRef] [PubMed] [Google Scholar]
  28. Durante M, Parodi K. Radioactive beams in particle therapy: Past, present, and future. Front Phys. 2020;28(8):00326. [Google Scholar]
  29. Parodi K, Polf JC. In vivo range verification in particle therapy. Med Phys. 2018;45(11):e1036–e1050. [CrossRef] [PubMed] [Google Scholar]
  30. Assmann W, Kellnberger S, Reinhardt S, Lehrack S, Edlich A, Thirolf PG, et al. Ionoacoustic characterization of the proton Bragg peak with submillimeter accuracy. Med Phys. 2015;42(2):567–574. [CrossRef] [PubMed] [Google Scholar]
  31. Jones KC, Seghal CM, Avery S. How proton pulse characteristics influence protoacoustic determination of proton-beam range: Simulation studies. Phys Med Biol. 2016;61(6):2213–2242. [CrossRef] [PubMed] [Google Scholar]
  32. Jones KC, Vander Stappen F, Bawiec CR, Janssens G, Lewin PA, Prieels D, et al. Experimental observation of acoustic emissions generated by a pulsed proton beam from a hospital-based clinical cyclotron. Med Phys. 2015;42(12):7090–7097. [CrossRef] [PubMed] [Google Scholar]
  33. Kellnberger S, Assmann W, Lehrack S, Reinhardt S, Thirolf P, Queirós D, et al. Ionoacoustic tomography of the proton Bragg peak in combination with ultrasound and optoacoustic imaging. Sci Rep. 2016;7(6):29305. [CrossRef] [PubMed] [Google Scholar]
  34. Lehrack S, Assmann W, Bertrand D, Henrotin S, Herault J, Heymans V, et al. Submillimeter ionoacoustic range determination for protons in water at a clinical synchrocyclotron. Phys Med Biol. 2017;62(17):L20–L30. [CrossRef] [PubMed] [Google Scholar]
  35. Patch SK, Kireeff Covo M, Jackson A, Qadadha YM, Campbell KS, Albright RA, et al. Thermoacoustic range verification using a clinical ultrasound array provides perfectly co-registered overlay of the Bragg peak onto an ultrasound image. Phys Med Biol. 2016;61(15):5621–5638. [CrossRef] [PubMed] [Google Scholar]
  36. Patch SK, Hoff DEM, Webb TB, Sobotka LG, Zhao T. Two-stage ionoacoustic range verification leveraging Monte Carlo and acoustic simulations to stably account for tissue inhomogeneity and accelerator-specific time structure – A simulation study. Med Phys. 2018;45(2):783–793. [CrossRef] [PubMed] [Google Scholar]
  37. Gensheimer MF, Yock TI, Liebsch NJ, Sharp GC, Paganetti H, Madan N, et al. In vivo proton beam range verification using spine MRI changes. Int J Radiat Oncol Biol Phys. 2010;78(1):268–275. [CrossRef] [PubMed] [Google Scholar]
  38. Scholey JE, Chandramohan D, Naren T, Liu W, Larson PEZ, Sudhyadhom A. Technical note: A methodology for improved accuracy in stopping power estimation using MRI and CT. Med Phys. 2021;48(1):342–353. [CrossRef] [PubMed] [Google Scholar]
  39. Yuan Y, Andronesi OC, Bortfeld TR, Richter C, Wolf R, Guimaraes AR, et al. Feasibility study of in vivo MRI based dosimetric verification of proton end-of-range for liver cancer patients. Radiother Oncol. 2013;106(3):378–382. [CrossRef] [PubMed] [Google Scholar]
  40. Lomax AJ. Myths and realities of range uncertainty. BJR. 2020;93(1107):20190582. [CrossRef] [PubMed] [Google Scholar]
  41. Moyers MF, Miller DW, Bush DA, Slater JD. Methodologies and tools for proton beam design for lung tumors. Int J Radiat Oncol Biol Phys 2001;49(5):1429–1438. [CrossRef] [PubMed] [Google Scholar]
  42. Park PC, Zhu XR, Lee AK, Sahoo N, Melancon AD, Zhang L, et al. A beam-specific planning target volume (PTV) design for proton therapy to account for setup and range uncertainties. Int J Radiat Oncol Biol Phys. 2012;82(2):e329–e336. [CrossRef] [PubMed] [Google Scholar]
  43. Amos RA, Diffenderfer ES, Johnson JEJ, Lin H, Perles LA, Wolfgang JA, et al. Proton beam therapy for pancreas cancer: PTCOG consensus recommendations for simulation, treatment planning and treatment delivery. Int J Radiat Oncol Biol Phys. 2022;114(3):e188–e189. [CrossRef] [Google Scholar]
  44. Deiter N, Chu F, Lenards N, Hunzeker A, Lang K, Mundy D. Evaluation of replanning in intensity-modulated proton therapy for oropharyngeal cancer: Factors influencing plan robustness. Med Dosim 2020;45(4):384–392. [CrossRef] [PubMed] [Google Scholar]
  45. Evans JD, Harper RH, Petersen M, Harmsen WS, Anand A, Hunzeker A, et al. The importance of verification CT-QA scans in patients treated with IMPT for head and neck cancers. Int J Part Ther. 2020;7(1):41–53. [CrossRef] [PubMed] [Google Scholar]
  46. Fakhraei S, Johnson JEJ, Tryggestad EJ, Mundy D, Shiraishi S, Haddock MG, et al. Retrospective analysis of replan frequency and causes in esophageal cancer patients treated with spot scanned proton therapy. Int J Radiat Oncol Biol Phys. 2022;114(3):e158–e159. [CrossRef] [Google Scholar]
  47. Moteabbed M, Trofimov A, Sharp GC, Wang Y, Zietman AL, Efstathiou JA, et al. Proton therapy of prostate cancer by anterior-oblique beams: Implications of setup and anatomy variations. Phys Med Biol, 2017;62(5):1644–1660. [CrossRef] [PubMed] [Google Scholar]
  48. Mundy D, Harper R, Deiter N. Analysis of spot scanning proton verification scan and re-plan frequency. In: Medical Physics. 111 River street, Hoboken 07030–5774, NJ, USA: Wiley; 2019. p. E250. [Google Scholar]
  49. Wagenaar D, Kierkels RGJ, van der Schaaf A, Meijers A, Scandurra D, Sijtsema NM, et al. Head and neck IMPT probabilistic dose accumulation: Feasibility of a 2 mm setup uncertainty setting. Radiother Oncol. 2021;154:45–52. [CrossRef] [PubMed] [Google Scholar]
  50. Wu RY, Liu AY, Sio TT, Blanchard P, Wages C, Amin MV, et al. Intensity-modulated proton therapy adaptive planning for patients with oropharyngeal cancer. Int J Part Ther. 2017;4(2):26–34. [CrossRef] [PubMed] [Google Scholar]
  51. Albertini F, Matter M, Nenoff L, Zhang Y, Lomax A. Online daily adaptive proton therapy. Br J Radiol. 2020;93(1107):20190594. [CrossRef] [PubMed] [Google Scholar]
  52. Jia S, Chen J, Ma N, Zhao J, Mao J, Jiang G, et al. Adaptive carbon ion radiotherapy for locally advanced non-small cell lung cancer: Organ-sparing potential and target coverage. Med Phys. 2022;49(6):3980–3989. [CrossRef] [PubMed] [Google Scholar]
  53. Li Y, Kubota Y, Okamoto M, Shiba S, Okazaki S, Matsui T, et al. Adaptive planning based on single beam optimization in passive scattering carbon ion radiotherapy for patients with pancreatic cancer. Radiat Oncol. 2021;16(1):111. [CrossRef] [PubMed] [Google Scholar]
  54. Paganetti H, Botas P, Sharp GC, Winey B. Adaptive proton therapy. Phys Med Biol. 2021;66(22):22TR01. [CrossRef] [Google Scholar]
  55. Trnkova P, Zhang Y, Toshito T, Heijmen B, Richter C, Aznar MC, et al. A survey of practice patterns for adaptive particle therapy for interfractional changes. Phys Imaging Radiat Oncol. 2023;28(26):100442. [CrossRef] [PubMed] [Google Scholar]
  56. Troost EGC, Menkel S, Tschiche M, Thiele J, Jaster M, Haak D, et al. Towards online adaptive proton therapy: First report of plan-library-based plan-of-the-day approach. Acta Oncol. 2022;61(2):231–234. [CrossRef] [PubMed] [Google Scholar]
  57. Yang M, Zhu XR, Park PC, Titt U, Mohan R, Virshup G, et al. Comprehensive analysis of proton range uncertainties related to patient stopping-power-ratio estimation using the stoichiometric calibration. Phys Med Biol. 2012;57(13):4095–4115. [CrossRef] [PubMed] [Google Scholar]
  58. Ainsley CG, Yeager CM. Practical considerations in the calibration of CT scanners for proton therapy. J Appl Clin Med Phys. 2014;15(3):4721. [Google Scholar]
  59. Schaffner B, Pedroni E. The precision of proton range calculations in proton radiotherapy treatment planning: experimental verification of the relation between CT-HU and proton stopping power. Phys Med Biol. 1998;43(6):1579–1592. [CrossRef] [PubMed] [Google Scholar]
  60. Bentefour EH, Shikui T, Prieels D, Lu HM. Effect of tissue heterogeneity on an in vivo range verification technique for proton therapy. Phys Med Biol. 2012;57(17):5473–5484. [CrossRef] [PubMed] [Google Scholar]
  61. Kruis MF. Improving radiation physics, tumor visualisation, and treatment quantification in radiotherapy with spectral or dual-energy CT. J Appl Clin Med Phys. 2022;23(1):e13468. [CrossRef] [PubMed] [Google Scholar]
  62. Peters N, Wohlfahrt P, Hofmann C, Möhler C, Menkel S, Tschiche M, et al. Reduction of clinical safety margins in proton therapy enabled by the clinical implementation of dual-energy CT for direct stopping-power prediction. Radiot Oncol. 2022;166:71–78. [CrossRef] [Google Scholar]
  63. Lomax AJ, Boehringer T, Coray A, Egger E, Goitein G, Grossmann M, et al. Intensity modulated proton therapy: A clinical example. Med Phys 2001;28(3):317–324. [CrossRef] [PubMed] [Google Scholar]
  64. Unkelbach J, Bortfeld T, Martin BC, Soukup M. Reducing the sensitivity of IMPT treatment plans to setup errors and range uncertainties via probabilistic treatment planning. Med Phys. 2009;36(1):149–163. [CrossRef] [PubMed] [Google Scholar]
  65. Unkelbach J, Chan TC, Bortfeld T. Accounting for range uncertainties in the optimization of intensity modulated proton therapy. Phys Med Biol. 2007;52(10):2755–2773. [CrossRef] [PubMed] [Google Scholar]
  66. Pflugfelder D, Wilkens JJ, Oelfke U. Worst case optimization: A method to account for uncertainties in the optimization of intensity modulated proton therapy. Phys Med Biol. 2008;53(6):1689–1700. [CrossRef] [PubMed] [Google Scholar]
  67. Pflugfelder D, Wilkens JJ, Szymanowski H, Oelfke U. Quantifying lateral tissue heterogeneities in hadron therapy. Med Phys. 2007;34(4):1506–1513. [CrossRef] [PubMed] [Google Scholar]
  68. Lomax AJ. Intensity modulated proton therapy and its sensitivity to treatment uncertainties 2: The potential effects of inter-fraction and inter-field motions. Phys Med Biol. 2008;53(4):1043–1056. [CrossRef] [PubMed] [Google Scholar]
  69. Fredriksson A. A characterization of robust radiation therapy treatment planning methods-from expected value to worst case optimization. Med Phys. 2012;39(8):5169–5181. [CrossRef] [PubMed] [Google Scholar]
  70. Albertini F, Hug EB, Lomax AJ. Is it necessary to plan with safety margins for actively scanned proton therapy? Phys Med Biol. 2011;56(14):4399–4413. [CrossRef] [PubMed] [Google Scholar]
  71. van Herk M, Remeijer P, Rasch C, Lebesque JV. The probability of correct target dosage: Dose-population histograms for deriving treatment margins in radiotherapy. Int J Radiat Oncol Biol Phys. 2000;47(4):1121–1135. [CrossRef] [PubMed] [Google Scholar]
  72. Lomax AJ. Intensity modulated proton therapy and its sensitivity to treatment uncertainties 1: The potential effects of calculational uncertainties. Phys Med Biol. 2000;53(4):1027–1042. [Google Scholar]
  73. Ding X, Li X, Zhang JM, Kabolizadeh P, Stevens C, Yan D. Spot-scanning proton arc (SPArc) therapy: The first robust and delivery-efficient spot-scanning proton arc therapy. Int J Radiat Oncol Biol Phys. 2016;96(5):1107–1116. [CrossRef] [PubMed] [Google Scholar]
  74. Reft C, Alecu R, Das IJ, Gerbi BJ, Keall P, Lief E, et al. Dosimetric considerations for patients with HIP prostheses undergoing pelvic irradiation. Report of the AAPM Radiation Therapy Committee Task Group 63. Med Phys. 2003;30:1162–1182. [CrossRef] [PubMed] [Google Scholar]
  75. Le Fèvre C, Lacornerie T, Noël G, Antoni D. Management of metallic implants in radiotherapy. Cancer/Radiothérapie 2022;26(1–2):411–416. [CrossRef] [Google Scholar]
  76. Czerska K, Emert F, Kopec R, Langen K, McClelland JR, Meijers A, et al. Clinical practice vs. state-of-the-art research and future visions: Report on the 4D treatment planning workshop for particle therapy – Edition 2018 and 2019. Phys Med. 2021;82:54–63. [CrossRef] [PubMed] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.